4 of 4 DemandTrendPermanent MLOps Jobs in South Wales

a related field Experience with multi-modal models that combine vision and language Strong grasp of data-centric AI practices - annotation tooling, prompt evaluation, and dataset curation Familiarity with MLOps tools (e.g. Weights & Biases, SageMaker, MLflow) Experience working in regulated sectors like insurance, banking, or property What You'll Be Doing This is a hands-on, high-impact role - you More ❯

Nice-to-Have Skills Experience with LangChain, LlamaIndex, or other RAG orchestration frameworks. Familiarity with model evaluation tools. Background in proptech, insurance, or financial services data ecosystems. Exposure to MLOps pipelines for continuous AI delivery in enterprise environments. What We Offer Flexible, hybrid working arrangements. Opportunity to deliver high-impact AI solutions for the property and financial services sectors. Culture More ❯

modern digital ecosystem using exciting technologies and do the best work of their careers. Your Key Responsibilities And Impact Designing, developing, and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK … and knowledge-sharing through comprehensive documentation, technical deep dives, brown bag sessions, internal workshops, and active mentorship of team members. Your Skills And Experience Extensive experience of DevOps/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services … AWS) - SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using More ❯

and do the best work of their careers. Your Key Responsibilities And Impact Lead the design, development, and evolution of robust tooling and platforms to support scalable Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and … culture through mentorship, knowledge sharing, and thought leadership via deep dives, brown bags, internal tech talks, and cross-team collaboration. Your Skills And Experience Extensive experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM … of cloud solution architecture. Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or Terraform in production environments. Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks. Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring. Deep experience More ❯